Deteksi Penyakit Diabetes Menggunakan Gaussian Naive Bayes, Regresi Logistik, dan Random Forest
Abstract
Diabetes is a very common health problem in the world. The number of people with diabetes is increasing from year to year. Therefore, it is necessary to realize the symptoms of diabetes as early as possible. Diabetes is a chronic disease characterized by high sugar levels in the blood. In this study, a system was made about a diabetes detection system based on numerical data using three methods. That three methods are Gaussian Naive Bayes method, Logistic Regression, and Random Forest by taking a dataset in the form of numerical data. The accuracy value on the data tested in this study using Gaussian Naive Bayes, Logistic Regression, Random Forest is 0.74; 0;78; 078.
Keywords: Gaussian Naive Bayes, Regresi Logistik, Random Forest
Published
2023-08-01
How to Cite
LESMANA, Kenny Belle; SUHARTANA, I Ketut Gede.
Deteksi Penyakit Diabetes Menggunakan Gaussian Naive Bayes, Regresi Logistik, dan Random Forest.
Jurnal Nasional Teknologi Informasi dan Aplikasnya, [S.l.], v. 1, n. 4, p. 1209-1214, aug. 2023.
ISSN 3032-1948.
Available at: <https://ojs.unud.ac.id/index.php/jnatia/article/view/102530>. Date accessed: 05 feb. 2025.
doi: https://doi.org/10.24843/JNATIA.2023.v01.i04.p25.
Section
Articles
